def test_backprop_multisample_zero_is_zero(self): lc = LinearCombination(4, 1) in_error_buffers = [np.zeros_like(self.X)] lc.backprop(self.theta, [self.X], self.T, np.zeros_like(self.T), in_error_buffers) grad = np.zeros_like(self.theta) lc.calculate_gradient(self.theta, grad, [self.X], self.T, in_error_buffers, np.zeros_like(self.T)) assert_allclose(in_error_buffers[0], np.zeros_like(self.X)) assert_allclose(grad, np.zeros_like(self.theta))